1. Field of the Invention
The present application relates to integrated circuit (IC) metrology, and more particularly to a sample structure profile determining method in an optical metrology system.
2. Related Art
The use of integrated circuit (IC) metrology has been successful for measuring sample structures. With the progress of deep sub-micron technology, the accuracy and efficiency of sample structure profile measurement are becoming increasingly critical. Examples of a sample structure comprise IC and test structure on a wafer.
For example, an optical metrology system employs a light source to beam light on a wafer structure. The diffracted light is then measured as a diffraction signal. In turn, regression-based methods or library-based methods can be used for determining the sample structure profile that matches the measured diffraction signal.
In one approach, in order to find a match, the measured diffraction signal is compared with previously generated (pre-generated) diffraction signals in a diffraction signal library. These pre-generated diffraction signals are typically simulated by using a rigorous coupled-wave analysis (RCWA) method.
An associated profile parameter, which characterizes a sample structure profile that corresponds to the nearest diffraction signal, is typically determined using pre-generated profile parameters found in a profile library. Furthermore, a profile parameter value change is calculated according to the diffraction signal change. This calculated profile parameter value change is evaluated to determine whether the profile parameter value change satisfies preset criteria. If the preset criteria are met, the new profile parameter value, which is calculated by adding the profile parameter value change to the associated profile parameter, is considered an acceptable approximation of the true profile parameter value corresponding to the measured diffraction signal. Otherwise, another diffraction signal is simulated based on this newly calculated profile parameter value by using RCWA method (or some other rigorous or approximation methods) in order to get a new diffraction signal change between the measured diffraction signal and the newly simulated diffraction signal. Several iterations of the profile parameter value computation and the diffraction signal simulation might be needed to finally converge to a profile parameter value that is considered an acceptable approximation of the true profile parameter value.
The conventional computing method for calculating a profile parameter value change from a diffraction signal change is to use the inverse of a Jacobian matrix from a conversion matrix library or directly calculated during the optimization process. (The definition of the inverse of a Jacobian matrix is provided in the detailed description.) The Jacobian matrix reflects sensitivities of sample structure profile parameters, meaning the magnitude of change of a diffraction signal corresponding to a change in a profile parameter value. However, when these sensitivities as reflected by the Jacobian matrix are highly correlated, this conventional approach may lack convergent speed and/or accuracy.
To increase the convergent speed, large number of CPUs or supercomputers are used. However, adding multiple CPUs or supercomputers not only increases the production cost, but also may not solve the profile parameter value convergence/inaccuracy problem. Moreover, beside the method described above, other optimization methods also do not solve the profile parameter value convergence/inaccuracy problem.
Through experiments, optical metrology engineers determine if the profile parameters in a profile library are generated from certain ways of parameterization of the profile, some of the corresponding conversion Jacobian matrices in the conversion matrix library contain highly correlated sensitivities of the sample structure profile parameters. On the other hand, if some other profile parameterization methods are used to generate the profiles in a profile library, the Jacobian matrix high correlation problem, which results in a greater number of iterations to be performed and thus increases processing time, might be avoided. Since no one knows exactly which sample structure profile parameterization will generate an accurate mapping and fast converging profile parameter in a profile library, each optical metrology engineer uses his or her own sample structure profile parameters relying on his or her past experience and know-how. As such, multiple profile libraries are typically created for the same sample structure structure. However, in so doing, having to perform optical metrology from different libraries causes inconsistency and confusion in the metrology industry.